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Machine Learning Engineer Interview Experience - United States

June 8, 2025
Negative ExperienceNo Offer

Process

The hiring manager is discouraging, creating an unwelcoming atmosphere that diminishes the enthusiasm of potential candidates.

The required properties and qualifications are not clearly listed in the job description, causing confusion and misalignment between the applicants' expectations and the role's actual demands. This lack of clarity leads to inefficiencies, as candidates may apply without fully understanding the job's requirements.

Furthermore, the interview process itself feels like a waste of time for both the applicants and the manager. Without a well-defined structure, it lacks focus and productivity, making it difficult to assess the true fit of a candidate effectively. This results in prolonged hiring timelines, increased frustration, and a potential loss of qualified talent who might seek more organized opportunities elsewhere.

Questions

Did you use Spark in your projects?

Interview Statistics

The following metrics were computed from 23 interview experiences for the Pinterest Machine Learning Engineer role in United States.

Success Rate

4%
Pass Rate

Pinterest's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.

Experience Rating

Positive39%
Neutral35%
Negative26%

Candidates reported having good feelings for Pinterest's Machine Learning Engineer interview process in United States.